import os

id_str = '06301330_atten3'

batch_size = 16
train_epochs = [2, 20, 20, 20]
lrs = [0.001, 0.0003, 0.0001, 0.0005]

e_train_epochs = [8]
e_lrs = [0.0003]

first_train_epochs = [2, 2, 2, 2]
first_lrs = [0.1, 0.03, 0.001, 0.0003]

eval_internal = 1
eval_print_batch_interval = 50
train_print_batch_interval = 50
persistent_internal = 40

consider_sent_types = ['impro', 'script']
vali_type = 'M'
test_type = 'F'
vali_test_ses = 3

train_k_prob = 0.5

os.environ["CUDA_VISIBLE_DEVICES"] = '0, 1, 2'
gpu_allow_growth = True

is_train = True

is_restore = False

# is_attention = True

is_shuffle_train = False

# attention_type = None
# attention_type = 'cnn'
# attention_type = 'simple'

restore_file = './output/bestacc-model/my-model-06180129_dann1'
restart_epoch_i = 0
first_train_restart_epoch_i = 0
e_train_restart_epoch_i = 0

out_put_log = id_str+'.log'

tf_log_dir = './output/tf_log/'

# Data configuration
# data_dir = '/Users/d/Project/emotions/data/Spectrogram_EN_Var'
data_dir = '/home/ddy/projects/emotions/data/Spectrogram_EN_Var'

classes = ['neu', 'ang', 'hap', 'sad']
sess = ['Ses01', 'Ses02', 'Ses03', 'Ses04', 'Ses05']
# consider_sent_types = ['impro']

is_post_calc_len = False

is_seq_len_weight = True

is_norm_weight = True

feature_size = 400

# cnn1_kernel = [1, 12, 1, 6]
# cnn2_kernel = [1, 8, 6, 10]
cnn1_kernel = [3, 3, 1, 8]
cnn2_kernel = [3, 3, 8, 8]
cnn3_kernel = [3, 3, 8, 16]
cnn4_kernel = [3, 3, 16, 16]

rnn_hidden_size = 128

attention_hidden_size = 10

fc1_b = 64

emos = ['neu', 'ang', 'hap', 'sad']

optimizer_type = 'adam'

persist_checkpoint_file = './output/p-model/my-model-' + id_str

gt_npy = './result/gt_' + id_str + '.npy'
pr_npy = './result/pr_' + id_str + '.npy'
sids_npy = './result/sids_' + id_str + '.npy'
ts_npy = './result/ts_' + id_str + '.npy'

# save alpha for train
alpha_gt_npy = './result/alpha_gt_' + id_str + '.npy'
alpha_pr_npy = './result/alpha_pr_' + id_str + '.npy'
alpha_npy = './result/alpha_' + id_str + '.npy'
alpha_seq_len_npy = './result/alpha_seq_len_' + id_str + '.npy'

# save alpha for test
a_npy = './result/a_' + id_str + '.npy'

persist_bestacc_file = './output/bestacc-model/my-model-' + id_str
persist_bestloss_file = './output/bestloss-model/my-model-' + id_str
